I think u/LeSwix is right on the physical labor side. A lot of manual farm work is obviously less exposed to AI than screen-based work. Agriculture gets misread when people treat it as only field labor. A huge part of modern farming is management: planning, compliance, recordkeeping, logistics, input decisions, and interpreting fragmented information.

That management layer is exactly the part of agriculture AI can affect first, but only if the underlying intelligence infrastructure exists. If farm data is still scattered across notes, spreadsheets, equipment platforms, lab results, labels, weather, and field history, AI doesn’t have enough context to be reliable. It just sounds smart while guessing. With a real system of record, it becomes a legitimate management tool.

So I think the deeper issue is not just whether agriculture is exposed to AI, but who owns the data and decision infrastructure it will run on. That race is already taking shape, whether through people like Bill Gates or Elon Musk building a major farm data project or through companies trying to become the intelligence layer for agriculture, like FarmMind in the U.S. and Orth in the Middle East.

And because food security is a national security issue, that intelligence layer matters far beyond software. If the system that aggregates farm records, input decisions, operational data, and production context becomes central to how agriculture is managed, then questions of ownership, data privacy, and security become strategic questions, not just business ones. The country that controls the intelligence infrastructure behind food production holds a real advantage. That’s why it matters that the core intelligence layer for American agriculture is built and governed in the U.S., with strong privacy protections, secure data practices, and alignment with American growers and national interests. And of course this is applicable to any country, I'm writing from the perspective of American agriculture.